Workshops

Silvino Fernandez Alzueta

Silvino Fernández is an R&D Engineer at the Global R&D Department of ArcelorMittal for more than 10 years. He develops his activity in the ArcelorMittal R&D Centre of Asturias, in the framework of the Business and TechnoEconomic project Area. He has a Master Science degree in Computer Science, obtained at University of Oviedo in Spain, and also a Ph.D. in Engineering Project Management obtained in 2015. His main research interests are in analytics, metaheuristics and swarm intelligence, and he has broad experience in using these kind of techniques in industrial environment to optimize production processes. His paper ‘Scheduling a Galvanizing Line by Ant Colony Optimization‘ obtained the best paper award in the ANTS conference in 2014.

Thomas Stützle

Thomas Stützle is a senior research associate of the Belgian F.R.S.-FNRS working at the IRIDIA laboratory of Université libre de Bruxelles (ULB), Belgium. He received the Diplom (German equivalent of M.S. degree) in business engineering from the Universität Karlsruhe (TH), Karlsruhe, Germany in 1994, and his PhD and his habilitation in computer science both from the Computer Science Department of Technische Universität Darmstadt, Germany, in 1998 and 2004, respectively. He is the co-author of two books about ``Stochastic Local Search: Foundations and Applications and ``Ant Colony Optimization and he has extensively published in the wider area of metaheuristics including 20 edited proceedings or books, 8 journal special issues, and more than 190 journal, conference articles and book chapters, many of which are highly cited. He is associate editor of Computational Intelligence, Swarm Intelligence, and Applied Mathematics and Computation and on the editorial board of seven other journals including Evolutionary Computation and Journal of Artificial Intelligence Research. His main research interests are in metaheuristics, swarm intelligence, methodologies for engineering stochastic local search algorithms, multi-objective optimization, and automatic algorithm configuration. In fact, since more than a decade he is interested in automatic algorithm configuration and design methodologies and he has contributed to some effective algorithm configuration techniques such as F-race, Iterated F-race and ParamILS. His 2002 GECCO paper on "A Racing Algorithm For Configuring Metaheuristics" (joint work with M. Birattari, L. Paquete, and K. Varrentrapp) has received the 2012 SIGEVO impact award.

Pablo Valledor Pellicer

Pablo Valledor is an R&D engineer of the Global R&D Asturias Centre at ArcelorMittal (world's leading integrated steel and mining company), working at the Business & Technoeconomic area. He obtained his MS degree in Computer Science in 2006 and his PhD on Business Management in 2015, both from the University of Oviedo. He worked for the R&D department of CTIC Foundation (Centre for the Development of Information and Communication Technologies in Asturias) until February 2007, when he joined ArcelorMittal. His main research interests are metaheuristics, multi-objective optimization, analytics and operations research.

Manuel López-Ibáñez

Dr. López-Ibáñez is a lecturer in the Decision and Cognitive Sciences Research Centre at the Alliance Manchester Business School, University of Manchester, UK. He received the M.S. degree in computer science from the University of Granada, Granada, Spain, in 2004, and the Ph.D. degree from Edinburgh Napier University, U.K., in 2009. He has published 17 journal papers, 6 book chapters and 36 papers in peer-reviewed proceedings of international conferences on diverse areas such as evolutionary algorithms, ant colony optimization, multi-objective optimization, pump scheduling and various combinatorial optimization problems. His current research interests are experimental analysis and the automatic configuration and design of stochastic optimization algorithms, for single and multi-objective problems. He is the lead developer and current maintainer of the irace software package for automatic algorithm configuration (http://iridia.ulb.ac.be/irace).

Daniel R. Tauritz

Daniel R. Tauritz is an Associate Professor in the Department of Computer Science at the Missouri University of Science and Technology (S&T), a contract scientist for Sandia National Laboratories, a former Guest Scientist at Los Alamos National Laboratory (LANL), the founding director of S&T's Natural Computation Laboratory, and founding academic director of the LANL/S&T Cyber Security Sciences Institute. He received his Ph.D. in 2002 from Leiden University for Adaptive Information Filtering employing a novel type of evolutionary algorithm. He served previously as GECCO 2010 Late Breaking Papers Chair, GECCO 2012 & 2013 GA Track Co-Chair, GECCO 2015 ECADA Workshop Co-Chair, GECCO 2015 MetaDeeP Workshop Co-Chair, GECCO 2015 Hyper-heuristics Tutorial co-instructor, and GECCO 2015 CBBOC Competition co-organizer. For several years he has served on the GECCO GA track program committee, the Congress on Evolutionary Computation program committee, and a variety of other international conference program committees. His research interests include the design of hyper-heuristics and self-configuring evolutionary algorithms and the application of computational intelligence techniques in cyber security, critical infrastructure protection, and program understanding. He was granted a US patent for an artificially intelligent rule-based system to assist teams in becoming more effective by improving the communication process between team members.

John R. Woodward

John R. Woodward s a lecturer at the University of Stirling, within the CHORDS group (http://chords.cs.stir.ac.uk/) and is employed on the DAASE project (http://daase.cs.ucl.ac.uk/), and for the previous four years was a lecturer with the University of Nottingham. He holds a BSc in Theoretical Physics, an MSc in Cognitive Science and a PhD in Computer Science, all from the University of Birmingham. His research interests include Automated Software Engineering, particularly Search Based Software Engineering, Artificial Intelligence/Machine Learning and in particular Genetic Programming. He has over 50 publications in Computer Science, Operations Research and Engineering which include both theoretical and empirical contributions, and given over 100 talks at International Conferences and as an invited speaker at Universities. He has worked in industrial, military, educational and academic settings, and been employed by EDS, CERN and RAF and three UK Universities.

Pietro S. Oliveto

Pietro S. Oliveto iHe is currently a Vice-Chancellor Fellow at the University of Sheffield, UK and has recently been awarded an EPSRC Early Career Fellowship which he will start in March 2015. He received the Laurea degree and PhD degree in computer science respectively from the University of Catania, Italy in 2005 and from the University of Birmingham, UK in 2009. From October 2007 to April 2008, he was a visiting researcher of the Ecient Algorithms and Complexity Theory Institute at the Department of Computer Science of the University of Dortmund where he collaborated with Prof. Ingo Wegener's research group.

His main research interest is the time complexity analysis of randomized search heuristics for combinatorial optimization problems. He has published several runtime analysis papers on Evolutionary Algorithms (EAs), Articial Immune Systems (AIS) and Ant Colony Optimization (ACO) algorithms for classical NP-Hard combinatorial optimization problems, a review paper of the field of time complexity analysis of EAs for combinatorial optimization problems and a book chapter containing a tutorial on the runtime analysis of EAs. He has won best paper awards at the GECCO08, ICARIS11 and GECCO14 conferences and got very close at CEC09 and at ECTA11 through best paper nominations.

Dr. Oliveto has given tutorials on the runtime complexity analysis of EAs at WCCI 2012, CEC 2013, GECCO 2013, WCCI 2014 and GECCO 2014. He is part of the Steering Committee of the annual workshop on Theory of Randomized Search Heuristics (ThRaSH), IEEE member and Chair of the IEEE CIS Task Force on Theoretical Foundations of Bio-inspired Computation.

Markus Wagner

Markus Wagner is a Senior Lecturer at the School of Computer Science, University of Adelaide, Australia. He has done his PhD studies at the Max Planck Institute for Informatics in Saarbruecken, Germany and at the University of Adelaide, Australia. For the outcomes of his studies, he has received the university's Doctoral Research Medal - the first for this school.
His research topics range from mathematical runtime analysis of heuristic optimisation algorithms and theory-guided algorithm design to applications of heuristic methods to renewable energy production, professional team cycling and software engineering. So far, he has been a program committee member 30 times, and he has written over 70 articles with over 70 different co-authors. He has contributed to GECCO as Workshop Chair in 2016 and 2017. He has chaired several education-related committees within the IEEE CIS, was Co-Chair of ACALCI 2017 and General Chair of ACALCI 2018.

Thomas Weise

Thomas Weise obtained the MSc in Computer Science in 2005 from the Chemnitz University of Technology and his PhD from the University of Kassel in 2009. He then joined the University of Science and Technology of China (USTC) as PostDoc and subsequently became Associate Professor at the USTC-Birmingham Joint Research Institute in Intelligent Computation and Its Applications (UBRI) at USTC. In 2016, he joined Hefei University as Full Professor to found the Institute of Applied Optimization at the Faculty of Computer Science and Technology. Prof. Weise has more than seven years of experience as a full time researcher in China, having contributed significantly both to fundamental as well as applied research. He has more than 80 scientific publications in international peer reviewed journals and conferences. His book "Global Optimization Algorithms – Theory and Application" has been cited more than 730 times. He has acted as reviewer, editor, or programme committee member at 70 different venues.

Borys Wróbel

Borys Wróbel's background is biology and computer science, and he works at the intersection between the two fields. His current research interest are computational properties of biologically-inspired models of computation (artificial gene regulatory networks and spiking neural networks), which involves building artificial life software platforms that use high performance computing and neuromorphic hardware. Borys graduated from the University of Gdansk (Poland) in 1997, was a Fulbright Visiting Researcher in the Salk Institute for Biological Studies in San Diego, CA, and later FEBS and EMBO Fellow at the Hebrew University of Jerusalem (Israel), Marie Curie Postdoctoral Fellow at the University of Valencia, and Sciex Fellow in the Insitute of Neuroinformatics at the University of Zurich and ETHZ (Switzerland). He is a member of the Global Young Academy, Intelligent Systems Applications Technical Committee of the Institute of Electrical and Electronics Engineers Computational Intelligence Society (since 2012), and Association for Computing Machinery Special Interest Group for Genetic and Evolutionary Computation.

Ales Zamuda

Ales Zamuda is an Assistant Professor and Researcher at University of Maribor (UM), Slovenia. He received Ph.D. (2012), M.Sc. (2008), and B.Sc. (2006) degrees in computer science from UM. He is management committee (MC) member for Slovenia at European Cooperation in Science (COST), actions CA15140 (ImAppNIO - Improving Applicability of Nature-Inspired Optimisation by Joining Theory and Practice) and IC1406 (cHiPSet - High-Performance Modelling and Simulation for Big Data Applications). He is IEEE Senior Member, IEEE Young Professionals Chair for Slovenia Section, IEEE CIS member, ACM SIGEVO member, ImAppNIO Benchmarks working group vice-chair, and editorial board member (associate editor) for Swarm and Evolutionary Computation (2017 IF=3.893). His areas of computer science applications include ecosystems, evolutionary algorithms, multicriterion optimization, artificial life, and computer animation; currently yielding h-index 16, 38 publications, and 742 citations on Scopus. He won IEEE R8 SPC 2007 award, IEEE CEC 2009 ECiDUE, 2016 Danubuius Young Scientist Award, and 1% top reviewer at 2017 Publons Peer Review Awards, including reviews for 40 journals and 65 conferences.

Anne Auger

Anne Auger is a permanent researcher at the French National Institute for Research in Computer Science and Control (INRIA). She received her diploma (2001) and PhD (2004) in mathematics from the Paris VI University. Before to join INRIA, she worked for two years (2004-2006) at ETH in Zurich. Her main research interest is stochastic continuous optimization including theoretical aspects and algorithm designs. She is a member of ACM-SIGECO executive committee and of the editorial board of Evolutionary Computation. She has been organizing the biannual Dagstuhl seminar "Theory of Evolutionary Algorithms" in 2008 and 2010 and served as track chair for the theory and ES track in 2011, 2013 and 2014. Together with Benjamin Doerr, she is editor of the book "Theory of Randomized Search Heuristics".

Julien Bect

Julien Bect is Associate Professor in CentraleSupélec, a French institute of research and higher education in engineering and science, and permanent researcher in L2S, the CentraleSupélec / CNRS / Paris-Sud University joint "Signals & Systems" laboratory. He received the Engineer's Degree (equivalent to a MSc in Electrical Engineering) from Supélec and the MSc in Applied Mathematics from Metz University, both in 2003. He received the PhD degree in 2007 from University of Paris-Sud (Paris XI, Orsay) for his work on stochastic hybrid systems. He has been working since then at Supélec (2007-2014), CentraleSupélec (2015-today), and IRT SystemX (2013--2016). His research interests include Gaussian processes interpolation and regression, sequential designs of (computer) experiments, sequential Monte Carlo algorithms, Bayesian uncertainty quantification (UQ), black-box optimization and reliability analysis.

Dimo Brockhoff

Dimo Brockhoff received his diploma in computer science from University of Dortmund, Germany in 2005 and his PhD (Dr. sc. ETH) from ETH Zurich,
Switzerland in 2009. Afterwards, he held two postdoctoral research positions in France at Inria Saclay Ile-de-France (2009-2010) and at Ecole
Polytechnique (2010-2011) before joining Inria in November 2011 as a permanent researcher (first in its Lille - Nord Europe research center and since October 2016 in the Saclay - Ile-de-France center). His research interests are focused on evolutionary multiobjective optimization (EMO), in particular on theoretical aspects of indicator-based search and on the benchmarking of blackbox algorithms in general.

Nikolaus Hansen

Nikolaus Hansen is a research scientist at INRIA, France. Educated in medicine and mathematics, he received a Ph.D. in civil engineering in 1998 from the Technical University Berlin under Ingo Rechenberg. Before he joined INRIA, he has been working in evolutionary computation, genomics and computational science at the Technical University Berlin, the InGene Institute of Genetic Medicine and the ETH Zurich. His main research interests are learning and adaptation in evolutionary computation and the development of algorithms applicable in practice. His best-known contribution to the field of evolutionary computation is the so-called Covariance Matrix Adaptation (CMA).

Rodolphe Le Riche

Rodolphe Le Riche is a CNRS senior researcher at LIMOS and the Ecole des Mines de Saint-Etienne, France since 2014. After a PhD in structural optimization at Virginia Tech, he worked as a post-doc at Ecole des Mines de Paris in model identification and joined the CNRS at INSA de Rouen, France in 1998. While staying at CNRS, Rodolphe moved to the Ecole des Mines de Saint-Etienne in 2002, became the leader of the applied mathematics department from 2009 to 2013, and acted as dean for research of the Henri Fayol Institute between 2014 and 2016. His current research interests are centered around optimization and statistical modeling with applications in engineering.

Victor Picheny

Victor Picheny is a permanent researcher at the French National Institute for
Agronomical research (INRA) in Toulouse, France, since 2012. He received
his diploma in engineering from the Ecole des Mines de Saint Etienne
(2005) and his PhD in applied mathematics from both the Ecole des Mines
and the University of Florida (2009). Before joining INRA, he held two
postdoctoral research positions in the Ecole Centrale de Paris
(2009-2011) and CERFACS (Toulouse, 2011-2012). His research interests
include Gaussian processes, Bayesian optimization, uncertainty
quantification and design of experiments.

Tea Tušar

Tea Tušar is a research fellow at the Department of Intelligent Systems of the Jožef Stefan Institute in Ljubljana, Slovenia. She received the BSc degree in Applied Mathematics and the MSc degree in Computer and Information Science from the University of Ljubljana. She was awarded the PhD degree in Information and Communication Technologies by the Jožef Stefan International Postgraduate School for her work on visualizing solution sets in multiobjective optimization. She has recently completed a one-year postdoctoral fellowship at Inria Lille in France where she worked on benchmarking multiobjective optimizers. Her research interests include evolutionary algorithms for singleobjective and multiobjective optimization with emphasis on visualizing and benchmarking their results and applying them to real-world problems.

She was involved in the organization of a number of workshops at previous GECCOs (BBOB, VizGEC, Women@GECCO and Student Workshop), she proposed and organized the Job Market at GECCO 2017 and held a tutorial on Visualization in Multiobjective Optimization at GECCO 2016.

Bilel Derbel

Bilel Derbel is an associate Professor at the Department of Computer Science at the University of Lille,
France. He is a permanent member of the BONUS ‘Big Optimization aNd Ultra-Scale Computing’ (ex DOLPHIN project) research group at Inria Lille Nord Europe and CRIStAL, CNRS. He is a co-founder member of the International Associated Lab (LIA-MODO) between Shinshu Univ., Japan, and Univ. Lille, France, on ‘Massive optimization and Computational Intelligence’. He is an associate editor of the IEEE Transactions on Systems Man and Cybernetics: Systems. His research topics are focused on the design and the analysis of combinatorial optimization algorithms and high performance computing. His current interests are on the design of cooperative, adaptive and distributed evolutionary algorithms for single- and multi- objective optimization.

Ke Li

Ke Li is a Lecturer (Assistant Professor) in Data Analytics at the Department of Computer Science, University of Exeter. He earned his PhD from City University of Hong Kong. Afterwards, he spent a year as a postdoctoral research associate at Michigan State University. Then, he moved to the UK and took the post of research fellow at University of Birmingham. His current research interests include the evolutionary multi-objective optimization, automatic problem solving, machine learning and applications in water engineering and software engineering.

Hui Li

Hui Li received the B.Sc. and M.Sc. degrees in applied mathematics from the School of Mathematics and Statistics, Xi’an Jiaotong University, Xi’an, China, in 1999 and 2002, respectively, and the Ph.D. in computer science from the University of Essex, Colchester, U.K., in 2008. From 2007 to 2010, he was a post-Doctoral Research Associate with the School of Computer Science, University of Nottingham, Nottingham, U.K. He is currently an Associate Professor with the School of Mathematics and Statistics, Xi’an Jiaotong University. His current research interests include evolutionary computation, multiobjective optimization, and machine learning. Dr. Li was a recipient of the 2010 IEEE Transactions on evolutionary Computation Outstanding Paper Award as one of the inventors for MOEA/D.

Xiaodong Li

Xiaodong Li received his B.Sc. degree from Xidian University, Xi'an, China, and Ph.D. degree in information science from University of Otago, Dunedin, New Zealand, respectively. Currently, he is a full professor at the School of Science (Computer Science and Software Engineering), RMIT University, Melbourne, Australia. His research interests include evolutionary computation, neural networks, complex systems, multiobjective optimization, and swarm intelligence. He serves as an Associate Editor of the IEEE Transactions on Evolutionary Computation, Swarm Intelligence (Springer), and International Journal of Swarm Intelligence Research. He is a founding member of IEEE CIS Task Force on Swarm Intelligence, a Vice-chair of IEEE CIS Task Force of Multi-Modal Optimization, and a former Chair of IEEE CIS Task Force on Large Scale Global Optimization. He was the General Chair of SEAL'08, a Program Co-Chair AI'09, and a Program Co-Chair for IEEE CEC’2012. He is the recipient of 2013 ACM SIGEVO Impact Award and 2017 IEEE CIS "IEEE Transactions on Evolutionary Computation Outstanding Paper Award".

Saúl Zapotecas

Saúl Zapotecas is a visiting Professor at Department of Applied Mathematics and Systems, Division of Natural Sciences and Engineering, Autonomous Metropolitan University, Cuajimalpa Campus (UAM-C). Saúl Zapotecas received the B.Sc. in Computer Sciences from the Meritorious Autonomous University of Puebla (BUAP). His M.Sc. and PhD in computer sciences from the Center for Research and Advanced Studies of the National Polytechnic Institute of Mexico (CINVESTAV-IPN). His current research interests include evolutionary computation, multi/many-objective optimization via decomposition, and multi- objective evolutionary algorithms assisted by surrogate models.

Qingfu Zhang

Qingfu Zhang is a Professor at the Department of Computer Science, City University of Hong Kong. His main research interests include evolutionary computation, optimization, neural networks, data analysis, and their applications. He is currently leading the Metaheuristic Optimization Research (MOP) Group in City University of Hong Kong. Professor Zhang is an Associate Editor of the IEEE Transactions on Evolutionary Computation and the IEEE Transactions Cybernetics. He was awarded the 2010 IEEE Transactions on Evolutionary Computation Outstanding Paper Award. He is on the list of the Thomson Reuters 2016 and 2017 highly cited researchers in computer science. He is an IEEE fellow.

Stéphane Doncieux

Stéphane Doncieux is Professeur des Universités (Professor) in Computer Science at Sorbonne Université, Paris, France. His research is mainly concerned with the use of evolutionary algorithms in the context of optimization or synthesis of robot controllers. He worked in a robotics context to design, for instance, controllers for flying robots, but also in the context of modelling where he worked on the use of multi-objective evolutionary algorithms to optimize and study computational models. More recently, he focused on the use of multi-objective approaches to tackle learning problems like premature convergence or generalization.
He is the head of the AMAC (Architecture and Models of Adaptation and Cognition) research team with 12 permanent researchers, 3 post-doc students and 13 PhD students. Researchers of the team work on different aspects of learning in the context of motion control and cognition, both from a computational neuroscience perspective and a robotics perspective.

Richard Duro

Richard J. Duro received a M.S. degree in Physics from the University of Santiago de Compostela, Spain, in 1989, and a PhD in Physics from the same University in 1992. He is currently a Full Professor in the Department of Computer Science and head of the Integrated Group for Engineering Research at the University of A Coruna, Spain. His research interests include cognitive, autonomous and evolutionary robotics, higher order neural network structures and multidimensional signal processing.

Joshua Auerbach

Dr. Joshua E. Auerbach, Ph.D. (Josh), is Assistant Professor in Computer Science and Innovation at Champlain College in Burlington, Vermont. Before starting at Champlain, Josh was a senior postdoctoral researcher with the Laboratory of Intelligent Systems (LIS) at the École Polytechnique Fédérale de Lausanne (EPFL) in Lausanne, Switzerland where he was funded under the European Union INSIGHT project. Prior to joining LIS, Josh was a member of the Morphology, Evolution & Cognition Laboratory at the University of Vermont where he earned a Graduate Certificate in Complex Systems in 2009, and an interdisciplinary Ph.D. in Computer Science in 2013 for his work on "The Evolution of Complexity in Autonomous Robots." Josh is the lead developer for the RoboGen open source hardware and software platform for the joint evolution of robot bodies and brains, he teaches classes across the spectrum of Computer Science disciplines, and he conducts research into various topics including questions related to the evolution of complexity, how evolution can contribute to learning, and how best to search interesting spaces (including robot morphologies and controllers).

Harold de Vladar

H.P. de Vladar studied Cell Biology and Statistical Physics later to become a theoretical evolutionary geneticist, following his PhD at the University of Groningen (2009). Most of de Vladar's work is on evolutionary biology, although often other subjects are also addressed. He currently works at Parmenides Foundation (Munich) for the consortium INSIGHT: Darwinian Neurodynamics, where his main goal is to understand aspects of cognition by using tools of evolutionary biology.

Antonio J. Fernández-Leiva

Antonio J. Fernández-Leiva received the Ph.D. degree in computer science from the University of Málaga (UMA), Málaga, Spain, in 2002. He is currently an Associate Professor in the Lenguajes y Ciencias de la Computación Department, MA. In the past, he worked in private companies as a computer engineer. His main areas of research involve both the application of metaheuristics techniques to combinatorial optimization and the employment of computational intelligence in videogames.

JJ Merelo

JJ Merelo is professor at the university of Granada. He has been involved in evolutionary computation for 20 years and not missed a PPSN since 2000, including the organisation of PPSN 2002 in Granada. He's the author of Algorithm::Evolutionary, a Perl evolutionary computation library and has given tutorials in GECCO, PPSN and CEC conferences. He's also been plenary speaker in ECTA 2013 and IDC 2014.

Pedro A. Castillo-Valdivieso

Pedro A. Castillo-Valdivieso received the B.Sc. degree in Computer Science and the Ph.D. degree, both from the University of Granada, Spain, in 1997 and 2000. His main research interests are in the fields of bio-inspired systems, hybrid system and combination of evolutionary algorithms and neural networks. He is currently Associate Professor at the Computer Architecture and Technology Department, University of Granada, Spain.

David Camacho-Fernández

David Camacho is currently working as Associate Professor in the Computer Science Department at Universidad Autonoma de Madrid (Spain) and Head of the Applied Intelligence & Data Analysis group. He received a Ph.D. in Computer Science (2001) from Universidad Carlos III de Madrid, and a B.S. in Physics (1994) from Universidad Complutense de Madrid. His research interests includes Data Mining (Clustering), Evolutionary Computation and Swarm Intelligence, Data mining and big Data, Machine Learning, and Video games.

Francisco Chávez de la O

Francisco Chávez received his Ph.D. in Computer Science from the University of Extremadura in 2012. Since 2001, he has belonged to the Department of Engineering of Computer and Telematic Systems of the University of Extremadura. He is currently a assistant professor and belongs to the Artificial Evolution Group. It has over 50 national and international publications. He has worked on several projects with computer science companies contributing technological transfer to the sector. He has three patents and his research lines are focused on systems based on fuzzy rules and diffuse genetic systems, image processing through deep learning and big data processing.

Ozgur Akman

Ozgur Akman is a Senior Lecturer in Mathematics at the University of Exeter. He has a BSc in Mathematics and a MSc in Bioengineering from Imperial College London, and a PhD in Mathematics from the University of Manchester. His research interests lie in the interface between applied mathematics, computer science and biology, focusing on the development of computational methods to systematically construct and analyse quantitative models of biochemical and neural networks. His earlier research used nonlinear dynamics techniques to identify the molecular mechanisms underlying the development of neurobiological motor disorders. A particular recent area of interest is the use of evolutionary computing methods to optimise large-scale systems biology models to experimental time series data. This important real-word optimisation problem is characterised by intrinsic uncertainty in the design space - due to the potential presence of multiple optima yielding similar fitness scores - and also in the objective space - due to experimental noise. 

Khulood Alyahya

Khulood Alyahya is a Research Fellow at the University of Exeter. She was awarded a PhD degree in Computer Science in 2016 from the University of Birmingham. She also has an MSc degree in Intelligent Systems Engineering from the same University where she was awarded the best student prize. Her PhD studies were on the landscape analysis of NP-hard problems. Her current research focuses on optimisation under multiple sources of uncertainty in both theoretical and applied settings, with application in the field of Computational Systems Biology. Her research includes extending landscape analysis tools to study the landscapes of robust optimisation problems.

Jürgen Branke

Jürgen Branke is Professor of Operational Research and Systems at Warwick Business School, University of Warwick, UK. He has been an active researcher in the field of Evolutionary Computation for over 20 years, has published over 160 papers in peer-reviewed journals and conferences, resulting in an H-Index of 48 (Google Scholar). His main research interests include optimization under uncertainty, simulation-based optimization and multi-objective optimization. Jürgen is Area Editor for the Journal of Heuristics, and Associate Editor for the Evolutionary Computation Journal, IEEE Transactions on Evolutionary Computation, and the Journal on Multi-Criteria Decision Analysis.

Kevin Doherty

Kevin Doherty is a Research Fellow at the University of Exeter. He has a degree in Mathematics and an MSc and PhD in Applied Mathematics from the National University of Ireland, Galway. Following the award of his PhD in 2014, he held a position as a post doctoral researcher in the Nutrition Physiology and Ingestive Behaviour (PNCA) lab, a joint research group operated between the institutions of INRA and AgroParisTech, before moving to Exeter in 2016. He is interested in the mathematical modelling of biological systems and, more recently, is especially interested in applying evolutionary computation to the problem of parameter estimation of such models.

Jonathan Fieldsend

Jonathan Fieldsend is Senior Lecturer in Computer Science at the University of Exeter. He has a degree in Economics from Durham University, a Masters in Computational Intelligence from the University of Plymouth and a PhD in Computer Science from the University of Exeter. He has held postdoctoral positions as a research fellow (working on the interface of Bayesian modelling and optimisation) and as a business fellow (focusing on knowledge transfer to industry) prior to his appointment to an academic position at Exeter.

He has published widely on theoretical and applied aspects of evolutionary multi-objective optimisation, and also in the field of machine learning — and has ongoing interests on the interface between these areas. His previous work has included developing a many-surrogate algorithm for multi-modal problems, and is currently working on surrogate-assisted learning for costly industrial design problems.

Work in these fields has also led to an interest in visualisation, which in turn has led to peer reviewed work on the application and comparison of existing visualisation techniques to new domains, and the investigation of novel visualisation techniques. He has been active within the evolutionary computation community as a reviewer and program committee member since 2003.

Giuseppe Carlo Marano

Dr. Giuseppe Carlo Marano obtained his Master in Civil Engineering (five year courses) from the Technical University of Bari, and his PhD in structural Engineering from the University of Florence, Italy. Dr. Marano is a Full Professor in the College of Civil Engineering at the Fuzhou University (P.R. China) where he teaches classes on Structural Engineering. Prior moving to Fuzhou University, he was Associate Professor in Structural Engineering at the Technical University of Bari. In the past he also served as Visiting at Cambridge University (UK) and Loughborough University (UK) and Hunan University (China). He is member of different international entities and committee, and is an active reviewer of international researches.
Dr. MARANO is an active member of the structural and seismic engineering research community, focusing on (a) random vibration approach to seismic engineering, (b) soft computing in structural engineering, (c) structural design optimization, (d) seismic protection using passive device and their optimization, (e) structural dynamic identification, (f) evolutionary computations. Among others, his publication track record includes more than 250 scientific publications (about 100 peer reviewed journal papers), 5 international patents, while he has presented his researches in different international venues.

Nikos D. Lagaros

Dr. Nikos D. LAGAROS obtained his BEng and PhD, both in Civil Engineering, from the National Technical University of Athens (NTUA), Greece. Dr. Lagaros is an Associate Professor in the Institute of Structural Analysis and Antiseismic Research in the School of Civil Engineering of NTUA where he teaches classes on Structural Analysis, Optimization and Computer Programming. He is the Director of the Personal Computers Laboratory, at the School of Civil Engineering of NTUA. Prior moving to NTUA, he was Assistant Professor in Civil Engineering at the University of Thessaly. In the past he also served as Visiting Professor at Department of Biological Engineering, Laboratory for Computational Biology & Biophysics, Massachusetts Institute of Technology, Boston, USA and the Department of Mechanical Engineering, Faculty of Engineering, McGill University, Montreal, Canada.
Dr. LAGAROS has provided consulting, peer-review and expert-witness services to private companies and federal government agencies in Greece and Internationally. A focus of his consulting work is the assessment of buildings after earthquake events and the development of technical software for structural analysis and design. Recently he released the first, real-world, optimum design computing platform for civil structural systems. He also acts as NSF Panellist, for reviewing proposals on seismic performance of masonry, concrete, and other structures, Directorate for Engineering-Civil, Mechanical and Manufacturing Innovation, in Washington DC, since 2010.
Dr. LAGAROS is an active member of the computational mechanics research community, focusing on (a) nonlinear dynamic analysis of concrete and steel structures under seismic loading, (b) performance-based earthquake engineering, (c) structural design optimization of real-world structures, (d) seismic risk and reliability analysis, (e) soft-computing in structural engineering, (f) fragility evaluation of reinforced concrete and steel structures, (g) inverse problems in structural dynamics, (h) parallel and distributed computing – Grid computing technologies, (i) evolutionary computations, (j) geotechnical earthquake engineering and (k) nano-modelling. Among others, his publication track record includes more than 95 peer reviewed journal paper, 10 books and 25 book chapters while he has presented his work in numerous international venues.

Koichi Nakayama

Koichi Nakayama is an Associate Professor at Saga University in Japan. He received his Ph.D from Kyoto University in 2005. He proposed a genetic algorithm to apply multi-agent systems. He was a researcher at ATR (Advanced Telecommunications Research Institute International) and NICT (National Institute of Information and Communications Technology). His research interest is to clear a cognitive process of an expert care giver by using evolutionary algorithms.

Chika Oshima

Chika Oshima is a visiting researcher at Saga University. She received her Ph.D from JAIST (Japan Advanced Institute of Science and Technology) in 2004. She was a researcher at ATR, NICT, and JSPS (Japan Society for the Promotion of Science). She analyzed a cognitive process that care givers decide an activity which suites for each dementia people in a care facility. Then, she developed a support system for elderly people to play the piano easily. She got the Best Paper Awards at ACM Multimedia 2004 and IARIA Global Health 2012.

Stefan Wagner

Stefan Wagner received his MSc in computer science in 2004 and his PhD in technical sciences in 2009, both from Johannes Kepler University Linz, Austria. From 2005 to 2009 he worked as associate professor for software project engineering and since 2009 as full professor for complex software systems at the Campus Hagenberg of the University of Applied Sciences Upper Austria. Dr. Wagner is one of the founders of the research group Heuristic and Evolutionary Algorithms Laboratory (HEAL) and is project manager and head architect of the open-source optimization environment HeuristicLab. He works as project manager and key researcher in several R&D projects on production and logistics optimization and his research interests are in the area of combinatorial optimization, evolutionary algorithms, computational intelligence, and parallel and distributed computing.

Michael Affenzeller

Michael Affenzeller has published several papers, journal articles and books dealing with theoretical and practical aspects of evolutionary computation, genetic algorithms, and meta-heuristics in general. In 2001 he received his PhD in engineering sciences and in 2004 he received his habilitation in applied systems engineering, both from the Johannes Kepler University Linz, Austria. Michael Affenzeller is professor at the University of Applied Sciences Upper Austria, Campus Hagenberg, and head of the research group Heuristic and Evolutionary Algorithms Laboratory (HEAL).

Boris Naujoks

Boris Naujoks is a professor for Applied Mathematics at TH Köln - Cologne University of Applied Sciences (CUAS). He joint CUAs directly after he received his PhD from Dortmund Technical University in 2011. During his time in Dortmund, Boris worked as a research assistant in different projects and gained industrial experience working for different SMEs. Meanwhile, he enjoys the combination of teaching mathematics as well as computer science and exploring EC and CI techniques at the Campus Gummersbach of CUAS. He focuses on multiobjective (evolutionary) optimization, in particular hypervolume based algorithms, and the (industrial) applicability of the explored methods.

Vanessa Volz

Vanessa Volz is a research assistant at TU Dortmund, Germany, with focus in computational intelligence. She holds B.Sc. degrees in Information Systems and in Computer Science from WWU Münster, Germany. She received an M.Sc. with distinction in Advanced Computing: Machine Learning, Data Mining and High Performance Computing from University of Bristol, UK in 2014 after completing a BigData internship at Brown University, RI, USA. Her current research focus is on employing surrogate-assisted evolutionary algorithms to obtain balance and robustness in systems with interacting human and artificial agents, especially in the context of games.

Tea Tušar

Tea Tušar is a research fellow at the Department of Intelligent Systems of the Jožef Stefan Institute in Ljubljana, Slovenia. She received the BSc degree in Applied Mathematics and the MSc degree in Computer and Information Science from the University of Ljubljana. She was awarded the PhD degree in Information and Communication Technologies by the Jožef Stefan International Postgraduate School for her work on visualizing solution sets in multiobjective optimization. She has recently completed a one-year postdoctoral fellowship at Inria Lille in France where she worked on benchmarking multiobjective optimizers. Her research interests include evolutionary algorithms for singleobjective and multiobjective optimization with emphasis on visualizing and benchmarking their results and applying them to real-world problems.

She was involved in the organization of a number of workshops at previous GECCOs (BBOB, VizGEC, Women@GECCO and Student Workshop), she proposed and organized the Job Market at GECCO 2017 and held a tutorial on Visualization in Multiobjective Optimization at GECCO 2016.

Pascal Kerschke

Pascal Kerschke is a PostDoc at the group of Information Systems and Statistics at the University of Muenster (Germany). Prior to completing his PhD studies in 2017, he has received a M.Sc. degree in "Data Sciences" (2013) from the Faculty of Statistics at the TU Dortmund (Germany). His main research interests are algorithm selection (for continuous or TSP problems), as well as Exploratory Landscape Analysis (ELA) for single- and multi-objective, continuous (Black-Box) optimization problems. Furthermore, he is one of the developers of related R-packages, such as "flacco", "smoof" and "mlr".

Riyad Alshammari

Riyad Alshammari is an Associate Professor in Computer Science and Joint-Associate Professor in Health Informatics at the Department of Health Informatics at the College of Public Health and Health Informatics, King Saud bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arabia. Dr. Alshammari is specialized in Network security, Network analysis and forensic, and machine learning. Dr. Alshammari's research interest include but not limited to the areas of Data mining, Machine Learning, Classification, Clinical Informatics, e- Health, Computer Network and Homeland Security. Dr. Alshammari is the Chairman of the Health Informatics Department and Director of Center of Excellence in Health Informatics, College of Public Health and Health Informatics, King Saud Bin Abdulaziz University For Health Sciences, Riyadh, Saudi Arabia. Dr. Alshammari has been elected as the President of Saudi Association for Health Informatics (SAHI).

Tokunbo Makanju

Tokunbo Makanju is Research Engineer with the Cybersecurity Laboratory at KDDI Research, Fuijimino-shi, Japan. His research interests are at the intersection of Big Data Analytics, Machine Learning, Network Management and Cybersecurity. Dr. Makanju is a member of the IEEE and the ACM.

Brad Alexander

Brad Alexander is a member of the Optimisation and Logistics Group at the University of Adelaide. His research interests include program optimisation, rewriting, genetic-programming (GP) - especially the discovery of recurrences and search-based-software-engineering. He is currently supervising projects in evolutionary art and in applications of search based software engineering to energy conservation and monitoring in mobile platforms. He has also supervised successful projects in the evolution of control algorithms for robots, the evolution of three-dimensional geological models, and the synthesis and optimisation of artificial water distribution networks, and using background optimisation to improve the performance of instruction set simulators (ISS)'s.

Saemundur O. Haraldsson

Saemundur O. Haraldsson is a research fellow at the University of Stirling. He has multiple publications on Genetic Improvement, including two that have received best paper awards; in last year's GI and ICTS4eHealth workshops. Additionally, he coauthored the first comprehensive survey on GI which was published in 2017. He has been invited to give talks on the subject in two Crest Open Workshops and for an industrial audience in Iceland. His PhD thesis (submitted in May 2017) details his work on the world's first live GI integration in an industrial application.

Markus Wagner

Markus Wagner is a Senior Lecturer at the School of Computer Science, University of Adelaide, Australia. He has done his PhD studies at the Max Planck Institute for Informatics in Saarbruecken, Germany and at the University of Adelaide, Australia. For the outcomes of his studies, he has received the university's Doctoral Research Medal - the first for this school.
His research topics range from mathematical runtime analysis of heuristic optimisation algorithms and theory-guided algorithm design to applications of heuristic methods to renewable energy production, professional team cycling and software engineering. So far, he has been a program committee member 30 times, and he has written over 70 articles with over 70 different co-authors. He has contributed to GECCO as Workshop Chair in 2016 and 2017. He has chaired several education-related committees within the IEEE CIS, was Co-Chair of ACALCI 2017 and General Chair of ACALCI 2018.

John R. Woodward

John R. Woodward s a lecturer at the University of Stirling, within the CHORDS group (http://chords.cs.stir.ac.uk/) and is employed on the DAASE project (http://daase.cs.ucl.ac.uk/), and for the previous four years was a lecturer with the University of Nottingham. He holds a BSc in Theoretical Physics, an MSc in Cognitive Science and a PhD in Computer Science, all from the University of Birmingham. His research interests include Automated Software Engineering, particularly Search Based Software Engineering, Artificial Intelligence/Machine Learning and in particular Genetic Programming. He has over 50 publications in Computer Science, Operations Research and Engineering which include both theoretical and empirical contributions, and given over 100 talks at International Conferences and as an invited speaker at Universities. He has worked in industrial, military, educational and academic settings, and been employed by EDS, CERN and RAF and three UK Universities.

Shin Yoo

Shin Yoo is an assistant professor at Korea Advanced Institute of Science and Technology, South Korea. He has extensively published on applications of metaheuristic search and evolutionary computation on software engineering, with a strong focus on testing and debugging. He received the Silver HUMIE at GECCO 2017 for his work on human competitive automated fault localisation using genetic programming. He has been the program co-chair of International Symposium on Search Based Software Engineering in 2014, and is the program co-chair of IEEE International Conference on Software Testing, Verification and Validation.

John McCall

John McCall is a Professor of Computing in the IDEAS Research Institute at Robert Gordon University in Scotland. Originally a pure mathematician (algebraic topology), he has over twenty years research experience in naturally-inspired computing. Major themes of his research include the development and analysis of novel metaheuristics, particularly markov-network EDAs, and probabilistic modelling for optimisation and learning. Application areas of his research include medical decision support, drilling rig market analysis, analysis of biological sequences, staff rostering and scheduling, image analysis and bio-control. Algorithms developed from his research have been implemented as commercial software. Prof. McCall has over 90 publications in books, international journals and conferences and he chairs the IEEE ECTC Task Force in Evolutionary Algorithms based on Probabilistic Models.

Nayat Sánchez-Pi

Nayat Sánchez-Pi is a Professor of Artificial Intelligence and Human-Computer Interaction at the Rio de Janeiro State University where she co-leads the Research on Intelligence and Optimisation Group (RIO). Prof. Sánchez-Pi research interests range from artificial intelligence, machine learning and data mining to ambient intelligence, ubiquitous computing, and multi-agent systems. She has led numerous energy and petroleum industry research projects applying evolutionary computation, machine learning, and other artificial intelligence methods.

Luis Martí

Luis Martí is Adjunct Professor at the Institute of Computing of the Universidade Federal Fluminense (UFF) in Niterói, Rio de Janeiro, Brazil where he co-leads the Research on Intelligence and Optimisation (RIO) Group. Luis' research is mainly concerned with evolutionary computation, evolutionary multi-objective optimization, machine learning, neural networks, and related topics. He having experience on those topics both at theoretical and applied levels.

Danilo Vasconcellos Vargas

Danilo Vasconcellos Vargas is an Assistant Professor at the Faculty of Information Science and Electrical Engineering, Kyushu University, Japan. He received the B.Eng. degree in computer engineering from the University of São Paulo, São Paulo, Brazil, in 2009, and both the M.Eng. and Ph.D. degree from Kyushu University, Fukuoka, Japan, in 2014 and 2016 respectively. His current research interests focus on general learning systems which include research in bio-inspired systems (evolutionary algorithms, neural networks, learning classifier systems, complex adaptive systems), the foundations of learning as well as intelligence (optimization, learning models, reward systems) and their applications.
He has authored more than 18 peer-reviewed papers, some of them in prestigious journals such as Evolutionary Computation (MIT Press) and IEEE Transactions of Neural Networks and Learning Systems. Moreover, his most recent investigation of deep neural models (one-pixel attack) was published on BBC News. He received prestigious awards and scholarships such as the German “Baden-Württemberg Scholarship” to study in Germany, the Japanese “Monbukagakusho Scholarship (MEXT)” to study in Japan for more than five years, among others.

More info: http://itslab.csce.kyushu-u.ac.jp/~vargas/.

Masaya Nakata

Masaya Nakata eceived the B.A. and M.Sc. degrees in informatics from the University of Electro- Communications, Chofu, Tokyo, Japan, in 2011 and 2013 respectively. He is the Ph.D. candidate in the University of Electro- Communications, the research fellow of Japan Society for the Promotion of Science, Chiyoda-ku, Tokyo, Japan, and a visiting student of the School of Engineering and Computer Science in Victoria University of Wellington from 2014. He was a visiting student of the Department of Electronics and Information, Politecnico di Milano, Milan, Italy, in 2013, and of the Department of Computer Science, University of Bristol, Bristol, UK, in 2014. His research interests are in evolutionary computation, reinforcement learning, data mining, more specifically, in learning classifier systems. He has received the best paper award and the IEEE Computational Intelligence Society Japan Chapter Young Researcher Award from the Japanese Symposium of Evolutionary Computation 2012. He is a co-organizer of International Workshop on Learning Classifier Systems (IWLCS) for 2015-2016.

Anthony Stein

Anthony Stein is a research associate and PhD student at the Faculty of Applied Computer Science, University of Augsburg, Germany. He received his BSc in Business Information Systems from the University of Applied Sciences in Augsburg in 2012. Afterward, he went to the University of Augsburg to proceed with his master's degree (MSc) in computer science with a minor in information economics which he received in 2014. Within his master's thesis, he dived into the nature of Learning Classifier Systems for the first time. Since then, he is a passionate follower of ongoing research in this field. Besides his position at the Organic Computing Group at the University of Augsburg, he is working on his PhD thesis in computer science. His research
focuses on the applicability of LCS in autonomous self-learning technical systems which are asked to act in real world environments that exhibit challenges such as data imbalance or non-stationarity. Therefore, in his work he makes use of interpolation techniques to change the means how classifiers are initialized or adequate actions are selected. A further research aspect he investigates is the question how learning classifier systems can be enhanced toward proactive knowledge construction. For the second time now, he also co-organizes the Workshop on Self- Optimization in Autonomic and Organic Computing Systems (SAOS).

Nadarajen Veerapen

Nadarajen Veerapen is a research fellow at the University of Stirling in Scotland. He holds a PhD in Computing Science from the University of Angers, France, where he worked on adaptive operator selection. He currently works on the “Cartography of computational search spaces” funded by the Leverhulme Trust. His research interests include local search, hybrid methods, search-based software engineering and visualisation. He has already served as Student Affairs Chair for GECCO 2017 and has previously co-organised the first two editions of the workshop on Landscape-Aware Heuristic Search at PPSN 2016 and GECCO 2017.

Arnaud Liefooghe

Arnaud Liefooghe is an Associate Professor (Maître de Conférences) at the University of Lille (France) since 2010. He is a member of the CRIStAL research center (UMR 9189, Univ Lille, CNRS, EC Lille) and of the Inria Lille - Nord Europe research center. He is also the co-director of the International Associated Laboratory LIA-MODŌ between Shinshu University (Japan) and the University of Lille (France). He received his PhD in computer science from the University of Lille (France) in 2009. In 2010, he was a post-doctoral researcher at the University of Coimbra (Portugal). His main research activities deal with the foundations, the design and the analysis of stochastic local search heuristic algorithms, with a particular interest in multi-objective optimization. He co-authored more than fifty scientific papers in international journals, book chapters and international conferences. He was awarded a best paper award at EvoCOP 2011 and at GECCO 2015. He co-organized two summer schools, the ThRaSH 2012 workshop, a special issue on EMO at EJOR, as well as special sessions or workshops at EURO 2012, MCDM 2013, LION 2013, CEC 2015 and 2017, as well as GECCO 2017. He has been a program committee member of more than twenty international conferences such as CEC, EMO, EvoCOP, GECCO, PPSN, and a regular journal reviewer from more than ten international journals. In 2018, he serves as a program chair for EvoCOP, and as a proceedings chair for GECCO.

Sébastien Verel

Sébastien Verel is a professor in Computer Science at the Université du Littoral Côte d'Opale, Calais, France, and previously at the University of Nice Sophia-Antipolis, France, from 2006 to 2013. He received a PhD in computer science from the University of Nice Sophia-Antipolis, France, in 2005. His PhD work was related to fitness landscape analysis in combinatorial optimization. He was an invited researcher in DOLPHIN Team at INRIA Lille Nord Europe, France from 2009 to 2011. His research interests are in the theory of evolutionary computation, multiobjective optimization, adaptive search, and complex systems. A large part of his research is related to fitness landscape analysis. He co-authored of a number of scientific papers in international journals, book chapters, book on complex systems, and international conferences. He is also involved in the co-organization EC summer schools, workshops, a special issue on EMO at EJOR, as well as special sessions in indifferent international conferences.

Gabriela Ochoa

Gabriela Ochoa is a Senior Lecturer in Computing Science at the University of Stirling, Scotland. She holds a PhD in Computing Science and Artificial Intelligence from the University of Sussex, UK. Her research interests lie in the foundations and application of evolutionary algorithms and heuristic search methods, with emphasis on autonomous (self-*) search, hyper-heuristics, fitness landscape analysis, and applications to combinatorial optimisation, healthcare, and software engineering. She has published over 90 scholarly papers and serves various program committees. She is associate editor of Evolutionary Computation (MIT Press), was involved in founding the Self-* Search track in 2011, and served as the tutorial chair at GECCO in 2012, 2013. She proposed the first Cross-domain Heuristic Search Challenge (CHeSC 2011) and was chair of EvoCOP 2014, EvoCOP 2015, FOGA 2015, and id serving as program chair for PPSN 2016.

Stephen L. Smith

Stephen L. Smith received a BSc in Computer Science and then an MSc and PhD in Electronic Engineering from the University of Kent, UK. He is currently a reader in the Department of Electronics at the University of York, UK.

Stephen's main research interests are in developing novel representations of evolutionary algorithms particularly with application to problems in medicine. His work is currently centered on the diagnosis of neurological dysfunction and analysis of mammograms. Stephen was program chair for the Euromicro Workshop on Medical Informatics, program chair and local organizer for the Sixth International Conference on Information Processing in Cells and Tissues (IPCAT) and guest editor for the subsequent special issue of BioSystems journal. More recently he was tutorial chair for the IEEE Congress on Evolutionary Computation (CEC) in 2009, local organiser for the International Conference on Evolvable Systems (ICES) in 2010 and co-general chair for the Ninth International Conference on Information Processing in Cells and Tissues (IPCAT) in April 2012. Stephen currently holds a Royal Academy of Engineering Enterprise Fellowship.

Stephen is co-founder and organizer of the MedGEC Workshop, which is now in its tenth year. He is also guest editor for a special issue of Genetic Programming and Evolvable Machines (Springer) on medical applications and co-editor of a book on the subject (John Wiley, November 2010).

Stephen is associate editor for the journal Genetic Programming and Evolvable Machines and a member of the editorial board for the International Journal of Computers in Healthcare and Neural Computing and Applications.

Stephen has some 75 refereed publications, is a Chartered Engineer and a fellow of the British Computer Society.

Stefano Cagnoni

Stefano Cagnoni graduated in Electronic Engineering at the University of Florence, Italy, where he has been a PhD student and a post-doc until 1997. In 1994 he was a visiting scientist at the Whitaker College Biomedical Imaging and Computation Laboratory at the Massachusetts Institute of Technology. Since 1997 he has been with the University of Parma, where he has been Associate Professor since 2004.

Recent research grants include: co-management of a project funded by Italian Railway Network Society (RFI) aimed at developing an automatic inspection system for train pantographs; a "Marie Curie Initial Training Network" grant, for a four-year research training project in Medical Imaging using Bio-Inspired and Soft Computing; a grant from "Compagnia diS. Paolo" on "Bioinformatic and experimental dissection of the signalling pathways underlying dendritic spine function".

He has been Editor-in-chief of the "Journal of Artificial Evolution and Applications" from 2007 to 2010. Since 1999, he has been chair of EvoIASP, an event dedicated to evolutionary computation for image analysis and signal processing, now a track of the EvoApplications conference. Since 2005, he has co-chaired MedGEC, workshop on medical applications of evolutionary computation at GECCO. Co-editor of special issues of journals dedicated to Evolutionary Computation for Image Analysis and Signal Processing. Member of the Editorial Board of the journals “Evolutionary Computation” and “Genetic Programming and Evolvable Machines”.

He has been awarded the "Evostar 2009 Award", in recognition of the most outstanding contribution to Evolutionary Computation.

Robert M. Patton

Dr. Patton received his Ph.D. in Computer Engineering with emphasis on Software Engineering from the University of Central Florida in 2002. In 2003, he joined the Applied Software Engineering Research group of Oak Ridge National Laboratory as a researcher. Dr. Patton primary research interests include data and event analytics, intelligent agents, computational intelligence, and nature-inspired computing. He currently is investigating novel approaches of evolutionary computation to the analysis of mammograms, abdominal aortic aneurysms, and traumatic brain injuries. In 2005, he served as a member of the organizing committee for the workshop on Ambient Intelligence - Agents for Ubiquitous Environments in conjunction with the 2005 Conference on Autonomous Agents and Multiagent Systems (AAMAS 2005).

William La Cava

Bill is a postdoctoral fellow at the University of Pennsylvania with the Institute for Biomedical Informatics. He received his Ph.D. from the University of Massachusetts Amherst under Professors Kourosh Danai and Lee Spector. His research focus is identifying causal models of disease from patient health records and genome wide association studies. His contributions in genetic programming include methods for local search, parent selection, and representation learning.

Randal Olson

Dr. Randal S. Olson is a Senior Data Scientist working with Prof. Jason H. Moore at the University of Pennsylvania Institute for Biomedical Informatics, where he develops state-of-the-art machine learning algorithms to solve biomedical problems. He specializes in artificial intelligence, machine learning, and data visualization, and regularly writes about his latest work on his personal blog, www.RandalOlson.com/blog. Dr. Olson has become known for computing optimal road trips around the world and solving "Where’s Waldo?," among other creative applications of machine learning, which have been featured all over the world and in the news, including the New York Times, Wired, FiveThirtyEight, and much more.

Dr. Olson works tirelessly to promote open and reproducible science, leading by example and openly publishing his work on GitHub and open access journals. He is also passionate about training the next generation of data scientists to be more efficient, effective, and collaborative in their work, and does so by writing online tutorials, recording video tutorials, teaching hands-on workshops, and mentoring local students in his research specialties.

Dr. Olson has been actively involved in GECCO for several years and won best paper awards at GECCO in 2014 and 2016 for his work in evolutionary agent-based modeling and automated machine learning.

Patryk Orzechowski

Dr. Patryk Orzechowski is a postdoctoral researcher in Artificial Intelligence at University of Pennsylvania. He obtained his Ph.D. in Computer Science and a Masters of Automation and Robotics from AGH University of Science and Technology in Krakow, Poland. His scientific interests are in the areas of machine learning, bioinformatics and artificial intelligence. He also specializes in data mining and mobile technologies.

Ryan Urbanowicz

Dr. Urbanowicz’s research is focused on bioinformatics, machine learning, epidemiology, data mining, and the development of a new learning classifier system that is maximally functional, accessible, and easier to use and interpret. He has written one of the most cited and regarded reviews of the Learning Classifier System research field as well as 12 additional peer-reviewed LCS research papers, has co-chaired the International Workshop on Learning Classifier Systems for the past 4 years, and has recently published and a new open source learning classifier system algorithm implemented in python, called ExSTraCS. He has also given several invited introductory lectures on LCS algorithms in addition to co-presenting this tutorial in 2013. Dr. Urbanowicz received a Bachelors and Masters of Biological Engineering from Cornell University, as well as a PhD in Genetics from Dartmouth College. Currently he is a post-doctoral researcher in the Geisel School of Medicine, about to transition to a new research position at the University of Pennsylvania, USA.

Ivanoe De Falco

Ivanoe De Falco received his Laurea degree in Electrical Engineering cum laude in 1987 at the University of Naples “Federico II.”, and is currently a senior researcher at the Institute for High-Performance Computing and Networking (ICAR) of the National Research Council of Italy (CNR). His main research fields include computational intelligence and parallel computing. He serves as an Associate Editor for the Applied Soft Computing journal (Elsevier), is a member of the World Federation on Soft Computing (WFSC), has been part of the Organizing or Scientific Committees for tens of international conferences or workshops, and has authored or coauthored about 120 papers in international journals, books, and conference proceedings.

Antonio Della Cioppa

Antonio Della Cioppa received the Laurea degree in physics and the Ph.D. degree in computer science, both from University of Naples “Federico II,” Naples, Italy, in 1993 and 1999, respectively.

From 1999 to 2003, he was a Postdoctoral Fellow at the Department of Computer Science and Electrical Engineering, University of Salerno, Salerno, Italy. In 2004, he joined the Department of Electrical and Information Engineering, University of Salerno, where he is currently Associate Professor of Computer Science and Artificial Intelligence. He is active in the fields of Artificial Intelligence and Cybernetics. His current research interests are in the fields of theoretical and computational physics (complexity, statistical mechanics of equilibrium and nonequilibrium phenomena, theory of dynamical systems, chaos), prebiotic evolution, Darwinian dynamics and speciation, evolutionary computation, and artificial life.

Dr. Della Cioppa is a member of the Association for Computing Machinery (ACM), the IEEE Computer Society, the IEEE Computational Intelligence Society. He serves as referee for many relevant international journals. He is also member of the program committee of many relevant international conferences such as the Genetic and Evolutionary Computation Conference and Conference on Evolutionary Computation.

Ernesto Tarantino

Ernesto Tarantino was born in S. Angelo a Cupolo, Italy, in 1961. He received the Laurea degree in Electrical Engineering in 1988 from University of Naples, Italy. He is currently a researcher at National Research Council of Italy. After completing his studies, he conducted research in parallel and distributed computing. During the past decade his research interests have been in the fields of theory and application of evolutionary techniques and related areas of computational intelligence. He is author of numerous scientific papers in international conferences and journals. He has served on several program committees of conferences in the area of evolutionary computation.

Umberto Scafuri

Umberto Scafuri was born in Baiano (AV) on May 21, 1957. He got his Laurea degree in Electrical Engineering at the University of Naples "Federico II" in 1985. He currently works as a technologist at the Institute of High Performance Computing and Networking (ICAR) of the National Research Council of Italy (CNR). His research activity is basically devoted to parallel and distributed architectures and evolutionary models.

P.G.M. Baltus

Peter Baltus was born on July 5th 1960 in Sittard and received his masters degree in Electrical Engineering from Eindhoven University of Technology in 1985, and his PhD degree from the same university in 2004. He worked for 22 years at Philips and later NXP in Eindhoven, Nijmegen, Tokyo and Sunnyvale in various functions, including research scientist, program manager, architect, domain manager, group leader and fellow in the areas of data converters, microcontroller architecture, digital design, software, and RF circuits and systems. In 2007 he started his current job at the Eindhoven University of Technology as professor in high-frequency electronics and chair of the mixed-signal micro-electronics group. He co-authored more than 100 papers and holds 16 US patents

Giovanni Iacca

Dr. Giovanni Iacca holds a MSc cum laude in Computer Engineering (2006) from the Technical University of Bari, IT, with a major in intelligent systems. From 2006 to 2009, he was a software engineer within the Italian National Research Council, where he worked on real-time systems for robotics and CNC applications. In 2011, Iacca earned a Ph.D. in Mathematical Information Technology from the University of Jyväskylä, FI, with a thesis on optimization algorithms for embedded systems. He then had several years of postdoctoral experience at INCAS³, NL (2012-2016); EPFL and University of Lausanne, CH (2013-2016); and RWTH Aachen University, DE (2017-2018). Currently, Iacca is Assistant Professor at the University of Trento, IT. His research focuses on computational intelligence, stochastic optimization, embedded systems, and distributed computing. To date, Iacca is coauthor of 60 peer-reviewed publications in these fields. He is actively involved in the organization of tracks and workshops at Evostar and GECCO, and he regularly serves as reviewer for several journals and conference committees.

Ahmed Hallawa

Ahmed Hallawa is a PhD candidate at the chair for Integrated Signal Processing Systems (ISS), RWTH Aachen University, Germany. He holds a BSc. degree in electric engineering from the German University in Cairo, Egypt and an MSc. degree from the university of Stuttgart, Germany. His main research interest is the use of machine learning in robotics, swarm intelligence, embedded systems and drug development. This involves research fields such as evolutionary computation, task distribution and collective behaviour, artificial neural networks and optimal control theory. He is currently taking part in the research activities of H2020-FETOPEN project “PHOENIX: Exploring the Unknown through Reincarnation and Co-evolution”.

Anil Yaman

Anil Yaman is a PhD researcher in Mathematics and Computer Science in the Eindhoven University of Technology. He holds a B.S. degree from the Karadeniz Technical University (Turkey, 2010), and an M.S. degree from the City College of the City University of New York (USA, 2014). From 2013 to 2015, Anil held a research position at the Department of Biomedical Informatics in Columbia University; and from 2015 to 2016, he joined to INCAS³, an independent research institute founded in Assen, the Nederlands. His main areas of research include topics in computational intelligence, specifically naturally inspired algorithms specializing in evolutionary computation, artificial neural networks, and swarm intelligence. Anil is currently involved in the H2020-FETOPEN project “PHOENIX: Exploring the Unknown through Reincarnation and Co-evolution”.

Alma Rahat

Alma Rahat is a Research Fellow at the University of Exeter, UK. He has a degree in Electronic Engineering from the University of Southampton, and a PhD in Computer Science from the University of Exeter. He has worked in the electronics industry as a product development engineer before starting his PhD. His research interests lie in fast hybrid optimisation methods, real-world problems and machine learning. Current research is on the use of surrogate-assisted optimisation approaches for expensive computational fluid dynamics design problems.

Richard Everson

Richard Everson is Professor of Machine Learning at the University of Exeter. He has a degree in Physics from Cambridge University and a PhD in Applied Mathematics from Leeds University. He worked at Brown and Yale Universities on fluid mechanics and data analysis problems until moving to Rockefeller University, New York, to work on optical imaging and modelling of the visual cortex. After working at Imperial College, London, he joined the Computer Science department at Exeter University.

His research interests lie in statistical pattern recognition, multi-objective optimisation and the links between them. Recent interests include the optimisation of the performance of classifiers, which can be viewed as a many-objective optimisation problem requiring novel methods for visualisation. Research on the construction of league tables has led to publications exploring the multi-objective nature and methods of visualising league tables. Current research is on surrogate methods for large optimisation problems, particularly computational fluid dynamics design optimisation.

Jonathan Fieldsend

Jonathan Fieldsend is Senior Lecturer in Computer Science at the University of Exeter. He has a degree in Economics from Durham University, a Masters in Computational Intelligence from the University of Plymouth and a PhD in Computer Science from the University of Exeter. He has held postdoctoral positions as a research fellow (working on the interface of Bayesian modelling and optimisation) and as a business fellow (focusing on knowledge transfer to industry) prior to his appointment to an academic position at Exeter.

He has published widely on theoretical and applied aspects of evolutionary multi-objective optimisation, and also in the field of machine learning — and has ongoing interests on the interface between these areas. His previous work has included developing a many-surrogate algorithm for multi-modal problems, and is currently working on surrogate-assisted learning for costly industrial design problems.

Work in these fields has also led to an interest in visualisation, which in turn has led to peer reviewed work on the application and comparison of existing visualisation techniques to new domains, and the investigation of novel visualisation techniques. He has been active within the evolutionary computation community as a reviewer and program committee member since 2003.

Handing Wang

1. Handing Wang received the B.Eng. and Ph.D. degrees from Xidian University, Xi'an, China, in 2010 and 2015. She is currently a research follow with the Department of Computer Science, University of Surrey, Guildford, UK. Her research interests include nature-inspired computation, multi- and many-objective optimization, multiple criteria decision making, and real-world problems. She has published over 10 papers in international journal, including IEEE Transactions on Evolutionary Computation (TEVC), IEEE Transactions on Cybernetics (TCYB), and Evolutionary Computation (ECJ).

Yaochu Jin

Yaochu Jin received the B.Sc., M.Sc., and Ph.D. degrees from Zhejiang University, China, in 1988, 1991, and 1996, respectively, and the Dr.-Ing. Degree from Ruhr University Bochum, Germany, in 2001. He is currently a Professor in Computational Intelligence and Head of the Nature Inspired Computing and Engineering (NICE) Group, Department of Computer Science, University of Surrey, UK. His research interests include computational intelligence, machine learning and computational neuroscience, in particular data-driven surrogate-assisted evolutionary optimization, multi-objective machine learning, evolutionary developmental systems, neural plasticity with applications to complex systems design, image processing, swarm robotics and bioinformatics.

He is the Editor-in-Chief of the IEEE Transactions on Cognitive and Developmental Systems, Co-Editor-in-Chief of Complex & Intelligent Systems, an Associate Editor of BioSystems, the IEEE Transactions on Cybernetics, IEEE Transactions on NanoBioscience and Soft Computing. He is also an Editorial Board Member of Evolutionary Computation. He is an Invited Plenary / Keynote Speaker at over 25 international conferences. He was the General Chair of IEEE CIBCB 2012 and IEEE SSCI 2016. He was the Vice President for Technical Activities and is an IEEE Distinguished Lecturer of the IEEE Computational Intelligence Society. He is the recipient of the 2014 and 2016 IEEE Computational Intelligence Magazine Outstanding Paper Award, the 2017 IEEE Transactions on Evolutionary Computation Outstanding Paper Award, and the Best Paper Award of 2010 CIBCB, and the Best Student Paper Award of FOCI 2007 and IEEE CEC 2017.

Dr Jin is a Fellow of IEEE and Fellow of BCS.

David Walker

David Walker is an Associate Research Fellow with the College of Engineering, Mathematics and Physical Sciences at the University of Exeter. The focus of his PhD was the understanding of many-objective populations. A principal component of his thesis involved visualising such populations and he is particularly interested in how evolutionary algorithms can be used to enhance visualisation methods. More recently, his research has investigated evolutionary methods for the data mining of many-objective populations, as well as for training artificial neural networks and designing novel nanomaterials. His general research interests include visualisation, evolutionary problem solving, particularly machine learning problems, techniques for identifying preference information in data and visualisation methods.

Richard Everson

Richard Everson is Professor of Machine Learning at the University of Exeter. He has a degree in Physics from Cambridge University and a PhD in Applied Mathematics from Leeds University. He worked at Brown and Yale Universities on fluid mechanics and data analysis problems until moving to Rockefeller University, New York, to work on optical imaging and modelling of the visual cortex. After working at Imperial College, London, he joined the Computer Science department at Exeter University.

His research interests lie in statistical pattern recognition, multi-objective optimisation and the links between them. Recent interests include the optimisation of the performance of classifiers, which can be viewed as a many-objective optimisation problem requiring novel methods for visualisation. Research on the construction of league tables has led to publications exploring the multi-objective nature and methods of visualising league tables. Current research is on surrogate methods for large optimisation problems, particularly computational fluid dynamics design optimisation.

Jonathan Fieldsend

Jonathan Fieldsend is Senior Lecturer in Computer Science at the University of Exeter. He has a degree in Economics from Durham University, a Masters in Computational Intelligence from the University of Plymouth and a PhD in Computer Science from the University of Exeter. He has held postdoctoral positions as a research fellow (working on the interface of Bayesian modelling and optimisation) and as a business fellow (focusing on knowledge transfer to industry) prior to his appointment to an academic position at Exeter.

He has published widely on theoretical and applied aspects of evolutionary multi-objective optimisation, and also in the field of machine learning — and has ongoing interests on the interface between these areas. His previous work has included developing a many-surrogate algorithm for multi-modal problems, and is currently working on surrogate-assisted learning for costly industrial design problems.

Work in these fields has also led to an interest in visualisation, which in turn has led to peer reviewed work on the application and comparison of existing visualisation techniques to new domains, and the investigation of novel visualisation techniques. He has been active within the evolutionary computation community as a reviewer and program committee member since 2003.

Akira Oyama

Akira Oyama is an associate professor at Institute of Space and Astronautical Science, Japan Aerospace Exploration Agency (JAXA) and the University of Tokyo in Japan. Previously, he worked for NASA Glenn research center in the U.S. from 2000 to 2003. His research interests include computational fluid dynamics and many/multi-objective design optimization in space engineering. He is the leader of "design innovation with multiobjective design exploration," one of the research topics of Japanese national supercomputer project "HPCI Strategic Programs for Innovative Research Field 4: Design Innovation" since 2010. He has published 265 conference papers and 33 refereed journal articles.

Koji Shimoyama

Koji Shimoyama is an associate professor in the Institute of Fluid Science, Tohoku University, Japan. He obtained his Ph.D. from the Department of Aeronautics and Astronautics, University of Tokyo, Japan, in 2006. Previously, he was a research assistant at JAXA, a research fellow at Tohoku University, a visiting scholar at Stanford University, United States, and an invited Professor at Ecole Centrale De Lyon, France. His research interests are multi-objective design exploration for engineering design, robust design optimization, and uncertainty quantification. He has performed collaborations with various industries in Japan regarding the application of EC and surrogate models for real-world product design and development.

Hemant Kumar Singh

Dr. Hemant Kumar Singh completed his Ph.D. from University of New South Wales (UNSW) Australia in 2011 and B.Tech in Mechanical Engineering from Indian Institute of Technology (IIT) Kanpur in 2007. Since 2013, he has worked with UNSW Australia as a Lecturer (2013-2017) and Senior Lecturer (2017-) in the School of Engineering and Information Technology. He also worked with GE Aviation at John F. Welch Technology Centre as a Lead Engineer during 2011-13. His research interests include development of evolutionary computation methods with a focus on engineering design optimization problems. He has over 50 refereed publications this area. He is the recipient of Australia Bicentennial Fellowship 2016, WCSMO Early Career Researcher Fellowship 2015 and The Australian Society for Defence Engineering Prize 2011 among others.

Kazuhisa Chiba

Kazuhisa Chiba is an associate professor in the graduate school of informatics and engineering, the University of Electro-Communications, Japan. Previously, he was a researcher at JAXA, a researcher at Mitsubishi Heavy Industries, and an associate professor at Hokkaido University of Science. His research interests are aerospace vehicles design via design informatics and multi/many-objective optimization.

Pramudita Satria Palar

Pramudita Satria Palar is a research fellow at the Institute of Fluid Science, Tohoku University, Japan. He obtained his Ph.D. from the Department of Aeronautics and Astronautics, University of Tokyo, Japan, in 2015. During his doctoral study, he was also a visiting researcher at Engineering Design Center of University of Cambridge, United Kingdom, and wrote several collaborative papers with the Center. His research interests are aerodynamic design optimization, surrogate-assisted optimization, and uncertainty quantification. He has published several journal and conference papers on the development and application of EC and surrogate models in the field of aerospace and biomedical engineering.